4 citations · 15 across the 6 of their papers we have counts for
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cs.CV2022
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces
Shitong Sun, Chenyang Si, Guile Wu +1
Conventional centralised deep learning paradigms are not feasible when data from different sources cannot be shared due to data privacy or transmission limitation. To resolve this…
cs.CV2022★ 3 cited
Self-Supervised Consistent Quantization for Fully Unsupervised Image Retrieval
Guile Wu, Chao Zhang, Stephan Liwicki
Unsupervised image retrieval aims to learn an efficient retrieval system without expensive data annotations, but most existing methods rely heavily on handcrafted feature descripto…
cs.CV2022★ 3 cited
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
Jian Hu, Haowen Zhong, Junchi Yan +3
Domain adaptation (DA) aims to transfer knowledge learned from a labeled source domain to an unlabeled or a less labeled but related target domain. Ideally, the source and target d…